The proposed project explores the relationship between schedules of age-specific demographic rates and the formation of dependent, or relational, social structures using demographic microsimulation. These social structures are the substrate upon which social diffusion processes spread and are of fundamental interest for understanding the transmission and, ultimately, the control and eradication of infectious disease. While the project is primarily methodological, it focuses its substantive application on understanding the role of demographic change in shaping patterns of tuberculosis (TB) epidemiology. The impact of changing demography on TB epidemiology is mediated through changes in the contact, or susceptibility structure of the population. The professional development plan articulated in this proposal addresses the following five objectives: (1) acquire the computer programming skills necessary to execute demographic microsimulations that explore the interaction between changing vital rates and the dependent social structures that are fundamental for the flow of information, support, and infection in human populations, (2) develop professional competence in stochastic analysis to complement computer simulation, (3) integrate more fully interests in social structure and human behavior with ongoing epidemiological research in infectious disease and its social consequences, (4) present research at professional meetings and publish in leading journals, (5) prepare a major grant to support an independent research program. Training components include mentorship, directed individual study with senior advisors, additional coursework in computer science, stochastic process and molecular epidemiology, and regular participation in population-related seminars in the San Francisco Bay Area. This research and professional development proposal builds upon and complements past work and training, providing novel tools for studying the critical intersection of aggregate demographic processes, micro-level social structure, and infection dynamics.